NSF-funded tool helps chips run faster, cooler and longer
From smartphones in our pockets to the powerful computers advancing artificial intelligence and quantum science, modern microchips are the engines of the digital age. Yet these systems face a fundamental challenge: managing the immense heat generated as processors grow faster and more complex, sometimes packing hundreds of thousands of cores onto a single chip. Without effective solutions, performance declines, energy is wasted and hardware reliability is compromised.
NSF-funded researchers at Clarkson University are addressing this challenge through TASChips, an open-source simulation tool that predicts in real time how heat builds up inside advanced processors. TASChips merges physics-based models with advanced reduced-order learning algorithms, delivering both accuracy and speed. It can identify thermal “hot spots” across complex chip architectures, enabling engineers to design systems that operate more efficiently, last longer and consume less energy.
Keeping powerful chips cool has always been a tough problem. Older tools that track heat either run quickly, but miss important details, or deliver accurate results so slowly that they cannot be used in practice. With today’s processors carrying more than 100,000 cores, that tradeoff no longer works. TASChips employs a range of learning models tailored to chips of varying complexity that capture the essential physics of heat transfer while running at much higher speeds. This approach produces near-direct numerical accuracy, fast enough to guide real-world decision-making. Engineers can use these results to redesign chips, adjust workloads dynamically in data centers, or avoid costly bottlenecks in high-performance systems. Such capabilities are essential in meeting the demands of the AI era.
Another barrier has been access. The most advanced heat-analysis tools are often locked behind expensive licenses and used only by large companies. TASChips changes that by being open source, free to download and released with clear instructions and examples. This means students, researchers and engineers anywhere can use the tool. It also ties directly into classroom and research programs, so the next generation of talent can learn with the same tools that will drive future breakthroughs.
To strengthen this link between innovation and education, TASChips will support workforce development through a series of workshops for up to 25 graduate students and postdoctoral researchers. Each participant will select a project aligned with their research expertise and carry out research that entails data collection, training, model parameter calculations and running simulations. By the end, participants will have gained hands-on experience applying a new tool to real problems, building skills that will carry forward into their careers.
The broader implications reach beyond engineering labs. Consumers benefit when everyday devices stay cooler and perform reliably. Businesses and communities benefit when data centers, which support everything from video streaming to financial transactions, operate more efficiently and at lower cost. And research sectors advancing AI and quantum technologies gain the reliable infrastructure needed to push the boundaries of discovery.
By combining rigorous science, open access, and education, the project provides a model for how federally supported research can translate into practical technologies that benefit society, industry and national competitiveness for years to come.